Contacts

Education

• BEng, Mechanical Engineering and Management, McMaster University
• MASc, Mechanical and Mechatronics Engineering, University of Waterloo (in progress)

Research interests

• Robotics
• Controls
• Machine learning

Education

• BASc, Mechanical Engineering, University of Waterloo (2020)

Research interests

• Robotics

Education

• 2007, PhD, Mechanical Engineering, University of Alberta
• 2003, MASc, Mechanical Engineering, University of Alberta
• 1988, MASc, Mechanical Engineering, KAIST
• 1985, BASc, Mechanical and Design Engineering, Seoul National University

Research Interests

• AI and machine learning algorithms
• Smart factory
• Application of AI to manufacturing
• Digital twin
• Non-destructive testing
• Therapeutic ultrasound (HIFU)

More about professor HJ Kwon

Professor Kwon received his BASc from Seoul National University, Korea in 1995 and MASc from KAIST, Korea in 1988. After over 10 years of industry experience, he received PhD from the University of Alberta, Canada. Prior to joining the University of Waterloo, he was a Natural Sciences and Engineering Research Council (NSERC) postdoctoral fellow at Caltech in Pasadena, USA. His research interests include AI for manufacturing, ultrasound nondestructive testing (NDT), on-board AI for NDT and non-invasive biomedical therapeutic and diagnostic methods. Professor Kwon is a licensed professional engineer in Ontario, Alberta and Korea (fluid machinery).

Professor HJ Kwon's Google Scholar

Education

• BSc, Mechanical Engineering, Islamic Azad University, Iran (2007)
• MSc, Mechanical Engineering, Islamic Azad University, Iran (2010)
• PhD, Petroleum Engineering, Curtin University (2017)

Research interests

• Digital twin
• AI-based predictive maintenance (PdM)

Iman Rostam Sowlat's Google Scholar

Education

• BSc, Mechanical Engineering, Yonsei University, Seoul (2010)
• MSc, Mechanical Engineering, Yonsei University, Seoul (2012)

Research interests

• Mobile robot

More about Jeong-woo Han

I am currently studying the field of mobile robots, particularly the problem of path and trajectory planning with dynamic obstacles. I have experience in robotics from my previous studies and work, which had mainly focused on serial robots including kinematics and dynamics, design, system integration, and some control.

Education

• BSc, Mechanical Engineering, Shahid Bahonar University of Kerman, Iran (2012)
• MSc, Mechanical Engineering, K. N. Toosi University of Technology, Iran (2015)
• PhD, Mechanical and Mechatronics Engineering, University of Waterloo (2020)

Research interests

• High intensity focused ultrasound

Moslem Sadeghi Goughari's Google Scholar

Education

• BEng, Mechanical Engineering, Anna University, India (2020)

Research interests

• Field-programmable gate array (FPGA)
• Printed circuit board (PCB) design

Education

• BSc, Mechanical Engineering, Khajeh Nasir Toosi University of Technology, Iran (2016)
• MSc, Mechanical and Mechatronics Engineering, University of Waterloo (2020)

Research interests

• AI-based non-destructive testing (NDT)
• AI-based high intensity focused ultrasound

Education

• BSc, Vehicle Engineering, (Automobile), Tongji University (2013)
• PhD, Mechanical and Mechatronics Engineering, University of Waterloo (2020)

Research interests

• Ultrasonic non-destructive testing (NDT)
• Field-programmable gate array (FPGA)-SoC system development
• Practical AI in manufacturing

More about Yanjun Qian

Yanjun received his PhD degree in Mechanical and Mechatronics Engineering at the University of Waterloo under the supervision of professor Hyock Ju Kwon. During his PhD studies, he developed two devices which were related to the non-destructive testing. The first one was a vibro-tactile sensor which can differentiate the stiffness of the soft material; and the second one was an ultrasonic non-destructive testing (NDT) device based on the FPGA-SoC platform. He worked closely with local industry during his study and accomplished several collaborative mechatronics-related projects, such as the development of a digital anglometer on the testing machine. Currently, he is working on practical AI solutions which can be applied to the production line.

Yanjun Qian's Google Scholar

Biography:

• BSc - Shiraz Electrical Engineering, Communications, Shiraz University, Iran (2004)
• MSc - Electrical Engineering, Communication Systems, Shiraz University, Iran (2007)
• PhD -Engineering, Wireless Communications, University of Technology Sydney, Australia (2017)

Research Interest:

Artificial Intelligence and Machine Learning, Robotics and Mobile Robots, Practical AI in manufacturing, (smart) Sensors, Ultrasonic non-destructive testing (NDT), Embedded Systems, Edge Computing, High performance computing (HPC)

More About Ali Rafiei:

Ali Received his PhD degree in Engineering, in Communications Networks. He was working on recovery of wireless communications and emergent cooperation in wireless sensor networks under supervision of A/Prof. Mehran Abolhasan at University of technology Sydney, Australia.  

Currently he is working on (smart) Sensors and Practical AI in manufacturing, NDT. 

‪Ali Rafiei - ‪Google Scholar